The color of a scene in an image appears different depending on what kind of light source (i.e., what kind of illuminant) was incident on the scene when the image was taken. This is because different illuminants such as incandescent light, fluorescent light, and daylight, have different power spectral distributions. White balance (WB) is the process of removing unrealistic color casts so that objects that appear white in a scene also appear white in an image of that scene. In CMOS image sensors, this problem is solved by adjusting the gains of the three primary color channels: red, green and blue. The capability to do white balancing automatically without user interference is known as automatic white balance (AWB).
The most widely used AWB process is based on the “gray-world” assumption; this assumption states that the average of the color in a scene is gray or colorless. Another commonly used assumption is the “white-world” assumption, which states that the brightest point in a scene is white, meaning that the red, green and blue values at the brightest point in a scene are equal to each other.
Although these assumptions are often true in many situations, they fail to provide proper white balance in images taken of a scene illuminated by multiple illuminants. For example, images having a wide shadow in an outdoor scene illuminated by sunshine fall into this category. When common AWB method are applied to these scenes, either only one part of an image is white balanced, leaving other parts having incorrect color casts, or neither parts is properly corrected as the AWB methods try to find a trade-off between different illuminants.